Accuracy of endoscopic ultrasound-fine needle aspiration of solid lesions over time: Experience from a new endoscopic ultrasound program at a Canadian community hospital
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: A Canadian Community Hospital launched a new Endoscopic Ultrasound (EUS) Program in 2011. The aim of this study was to report the accuracy of EUS-fine needle aspiration (EUS-FNA) of solid lesions over time as it pertains to cytotechnologists' involvement and learning curves. METHODS: The electronic medical records of patients that had a EUS from July 2011 to January 2014 were retrospectively reviewed. Only solid lesions with FNA sampling were included in the study. The primary outcome assessed was the accuracy of specimen acquisition for pathological review. The secondary outcome was diagnostic accuracy. Cases were separated by chronological order into thirds for the assessment of learning curves. Cytotechnologists' involvement was correlated to determine its impact on accuracy. RESULTS: Two hundred and seventy-one EUS-FNA procedures were completed for solid lesions. Cytotechnologists' involvement resulted in a specimen acquisition accuracy of 82.6%, compared with 68.8% without a cytotechnologist (P = 0.009; 95% confidence interval [CI] 3.2%-25.0%). Diagnostic accuracy was 74.2% with a cytotechnologist while 62.4% without a cytotechnologist (P = 0.038; 95% CI 0.3%-23.7%). The specimen acquisition accuracy increased from 73.2% from the first third of cases to 92.3% for the last third with a cytotechnologist (P = 0.004; 95% CI 6%-33.0%). Without a cytotechnologist, the specimen accuracy was 67.6% for the first third while 57.7% for the last third of cases (P = 0.434; 95% CI - 33.9-14.4%). In the multivariable regression analysis, after adjusting for other predictors, a present cytotechnologist (P = 0.022) and lesion size 21 mm-30 mm (P = 0.039) and >30 mm (P = 0.001) were significantly associated with increased specimen acquisition accuracy. Only a present cytotechnologist (P = 0.046) was significantly associated with increased diagnostic accuracy. INTERPRETATION: Cytotechnologists' involvement significantly improved the accuracy of specimen acquisition. Although accuracy was impacted by a cytotechnologist learning curve, our results highlight the importance of a cytotechnologist being present for EUS-FNA sampling of solid lesions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".